A Bayesian-Network-based Approach to Risk Analysis in Runway Excursions. (27th March 2019)
- Record Type:
- Journal Article
- Title:
- A Bayesian-Network-based Approach to Risk Analysis in Runway Excursions. (27th March 2019)
- Main Title:
- A Bayesian-Network-based Approach to Risk Analysis in Runway Excursions
- Authors:
- Calle-Alonso, Fernando
Pérez, Carlos J.
Ayra, Eduardo S. - Abstract:
- Abstract : Aircraft accidents are extremely rare in the aviation sector. However, their consequences can be very dramatic. One of the most important problems is runway excursions, when an aircraft exceeds the end (overrun) or the side (veer-off) of the runway. After performing exploratory analysis and hypothesis tests, a Bayesian-network-based approach was considered to provide information from risk scenarios involving landing procedures. The method was applied to a real database containing key variables related to landing operations on three runways. The objective was to analyse the effects over runway overrun excursions of failing to fulfil expert recommendations upon landing. For this purpose, the most influential variables were analysed statistically, and several scenarios were built, leading to a runway ranking based on the risk assessed.
- Is Part Of:
- Journal of navigation. Volume 72:Number 5(2019)
- Journal:
- Journal of navigation
- Issue:
- Volume 72:Number 5(2019)
- Issue Display:
- Volume 72, Issue 5 (2019)
- Year:
- 2019
- Volume:
- 72
- Issue:
- 5
- Issue Sort Value:
- 2019-0072-0005-0000
- Page Start:
- 1121
- Page End:
- 1139
- Publication Date:
- 2019-03-27
- Subjects:
- Aviation, -- Safety, -- Bayesian estimation, -- Risk Minimisation, -- Runway excursion
Navigation -- Periodicals
623.8905 - Journal URLs:
- https://www.cambridge.org/core/journals/journal-of-navigation ↗
- DOI:
- 10.1017/S0373463319000109 ↗
- Languages:
- English
- ISSNs:
- 0373-4633
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library STI - ELD Digital store
- Ingest File:
- 11263.xml